Obeng William obengwilliam

install using pyenv on mac 11

pyenv install --patch 3.8.3 < <(curl -sSL https://github.com/python/cpython/commit/8ea6353.patch)

Move tabs

in command mode type tabm [index from 0 to n represent tabs from your left to right]

Windows

Swap Ctrl + W + R

Badges

License

Version

Kubectl output options

Let's look at some basic kubectl output options.

Our intention is to list nodes (with their AWS InstanceId) and Pods (sorted by node).

We can start with:

kubectl get no

Activate MS Office 2019/2016 for macOS - Microsoft_Office_2019_VL_Serializer

Office 2019 above

2019-06-03

Note that Office2019 DO NOT support activate via simple copy/paste plist license file which is the simplest way to activate Office 2016. Fortunately, you can also use the VL Serializer tool, just install Office 2019 and Serializer, then run Serializer to activate.

	self.init_plot(self.FEATURES)

	has_converged = False
	iter = 1

	while not has_converged:
	print(f"iter {iter}")

	minibatch = random.sample(range(0, self.DATAPOINTS), self.MINIBATCH_SIZE)
	for k in range(self.FEATURES):

	import { Link } from 'react-router-dom'
	import { Badge, Col, Menu } from 'antd'

	const StyledBadge = styled(Badge)`
	.ant-badge-count {
	background-color: #7ECBBF;
	color: white;
	box-shadow: 0 0 0 1px #d9d9d9 inset;
	}
	`

	'use strict';

	const mongoose = require('mongoose');

	run().catch(err => console.log(err));

	async function run() {
	mongoose.set('useUnifiedTopology', true);
	mongoose.set('useNewUrlParser', true);

	/*
	* This script will download a package (and all of its dependencies) from the
	* online NPM registry, then create a gzip'd tarball containing that package
	* and all of its dependencies. This archive can then be copied to a machine
	* without internet access and installed using npm.
	*
	* The idea is pretty simple:
	* - npm install [package]
	* - rewrite [package]/package.json to copy dependencies to bundleDependencies
	* - npm pack [package]

	Isomap is a nonlinear dimensionality reduction method.
	The algorithm provides a simple method for estimating the intrinsic geometry of a data manifold based on a rough estimate
	of each data point’s neighbours